Deposition of anionic conjugated poly(phenylenevinylene) onto silica nanoparticles via electrostatic interactions — Assembly and single-particle spectroscopy
Bibliographic record
Abstract
Fluorescent nanoparticles were prepared via adsorption of the conjugated polyelectrolyte poly[5-methoxy-2-(3-sulfopropoxy)-1,4-phenylenevinylene] (MPS-PPV) onto 50 and 100 nm aminosilane functionalized silica beads. The particles were investigated via ensemble and single-molecule or -particle spectroscopy techniques to quantify the effect of the silica bead core on the exciton migration efficiency within the polymer. Ensemble emission spectra and ensemble fluorescence quenching studies with methyl viologen are consistent with good exciton migration along the polymer in the polymer-coated bead. The silica nanobead scaffolding preserves the sensitivity of the free polymer and provides a controllable architecture that minimizes nonspecific interactions. Single-particle spectroscopy studies were conducted on particles immobilized onto the positively charged surface of glass cover slips. Particle immobilization enabled us to monitor the effect of oxygen scavenger solutions on individual particles by changing the surrounding solution. The intensity–time trajectories of individual beads provide a mechanism of signal transduction with potential applications in multiplexing studies. Hundreds of individual beads can be imaged in a rapid parallel fashion.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".